search for: tchur

...the low-volume gestalt-system-news list in order to receive announcements. Please see the project Web page at http://gestalt-system.sourceforge.net for details of how to subscribe. If you wish your feedback to be kept private, you can respond to the authors of the project proposal: Tim Churches at tchur at bigpond.com and Karsten M. Self at kmself at ix.netcom.com Please note that the Reply-To address of this message is set to gestalt-system-discuss at lists.sourceforge.net which means that your reply will by default be distributed to all subscribers to this list. You may wish to change the addre...

Version 2.1.1 Platforms: all What is the trellis parameter (or is there a trellis parameter) to set the leading (the gap between lines) when long axis values labels or panel header labels wrap over more than one line? By default, there is a huge gap between lines, and much looking and experimentation has not revealed to me a suitable parameter to adjust this. Tim C

A recent paper from Google Labs, interesting in many respects, not the least the exclusive use of R for data analysis and graphics (alas not cited in the approved manner): http://labs.google.com/papers/disk_failures.pdf Perhaps some of the eminences grises of the R Foundation could prevail upon Google to make some the data reported in the paper available for inclusion in an R library or two, for

Hi all -- I'm using trellis to generate bar charts, but there's no built-in function to generate error bars or confidence intervals, as far as I can tell. I assumed I could just write my own panel function to add them, so I searched the archive, and found a posting from the author of the package stating "... placing multiple bars side by side needs specialized calculations, which

We are using glm() to models to counts of deaths due to rare causes using a log link and Poisson error distribution, with population as the offset. Approximate confidence intervals for the parameter estimates are easy to calculate using a standard normal deviate, but obviously when the counts of deaths are small (which is why we are using Poisson regression), these intervals are very approximate

...me amount on two S Plus licenses for Windows (which are not exactly cheap since we are a government department, although since we started paying for SAS each year nothing shocks us any more...). Tim Churches Epidemiology and Health Surveillance Branch NSW Health Department Sydney, Australia Email: tchur at doh.health.nsw.gov.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !)...

I am trying to add confidence (error) bars to lattice barcharts (and dotplots, and xyplots). I found this helpful message from Deepayan Sarkar and based teh code below on it: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/50299.html However, I can't get it to work with groups, as illustrated. I am sure I am missing something elementary, but I am unsure what. Using R 2.1.1 on various

I've been a R-user for quite some time. The graphic on the home page looks a bit in need of polish so I applied some antialiased transformations that Peter Dalgaard has previously posted to R-help for improving graphic quality. I had to change the margins a bit, but here is what it looks like: http://www.broad.mit.edu/~finnyk/Rhome.jpg Personally, I think it looks much better. Because

A question for a (experienced) user of the RPython package on linux. I'm trying to call R from python on a linux (Suse 7.3) box. After installing R CMD INSTALL -c RSPython_0.5-2.tar.gz I start python and do: >>> import sys >>> sys.path.append('/usr/local/lib/R/library/RSPython') >>> sys.path.append('/usr/local/lib/R/library/RSPython/Python')

Any advice, tips, clues or pointers to resources on how best to speed up or, better still, avoid the loops in the following example code much appreciated. My actual dataset has several tens of thousands of rows and lots of columns, and these loops take a rather long time to run. Everything else which I need to do is done using vectors and those parts all run very quickly indeed. I spent quite a

Walter Moreira wrote: > I wrote a small extension module for using the R programming language from > within Python. It makes it possible to use the huge mathematical and > statistical library of R from Python, almost whitout any changes from the text > of R manuals. > > As a side effect, it is also possible to use the full graphics capabilities of > R, which are extremely

mantelhaen.test() gives the exact conditional p-value (for independence) and confidence intervals (CIs)for the common odds ratio for a stratified 2x2 table. The epitools package by Tomas Aragon (available via CRAN) contains functions which use fisher.test() to calculate mid-p exact p-values and CIs for the CMLE odds ratio for a single 2x2 table. The mid-p p-value for independence for a stratified

Many thanks to the R core team for their work on R connections. I was delighted to discover that it is now possible to remote-control R-1.3.0 via a socket connection - something which Brian Ripley noted was not yet possible with R-1.2.0 back in January 2001 in the first R News newsletter. How? Just substitute source() for readLines() in last few lines of the example for a socket connection given

We have two time series: the first is a series of weekly counts of isolates of RSV (respiratory syncytial virus) by pathology laboratories, and the second is a series of weekly counts of cases of bronchiolitis in young children presenting to hospital emergency departments. Bronchiolitis in young children is usually caused by RSV infection, and simple visual inspection reveals a very close

R V2.0.1 on Windows XP. I have read the help pages on strptime() over and over, but can't understand why strptime() is producing the following results. > v <- format("2002-11-31", format="%Y-%m-%d") > v [1] "2002-11-31" > factor(v, levels=v) [1] 2002-11-31 Levels: 2002-11-31 > x <- strptime("2002-11-31",

This news item in a data mining newsletter makes various claims for a technique called "Reduced Error Logistic Regression": http://www.kdnuggets.com/news/2007/n08/12i.html In brief, are these (ambitious) claims justified and if so, has this technique been implemented in R (or does anyone have any plans to do so)? Tim C